Researchers have developed an easy-to-use optical chip that can configure itself to achieve various functions. The positive real-valued matrix computation they have achieved gives the chip the ...

Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs large-scale nonlinear computations using linear materials. Reported in ...

Diffractive Deep Neural Networks (D 2 NN) 1 have emerged as an optical machine learning framework that parameterizes a given inference or computational task as a function of the physical traits of a ...

Over the past four years, The Photonics100 has recognised hundreds of outstanding individuals from academia, industry, start-ups and research organisations worldwide. Together, they represent the ...

Controlled disorder enables multiple optical functions within a single compact device Mosaic metasurfaces reduce space requirements for complex light manipulation tasks Eleven optical functions ...

We introduce the refractiveindex.info database, a comprehensive open-source repository containing optical constants for a wide array of materials, and describe in detail the underlying dataset. This ...

Optical coherence extends beyond lasers, with partially coherent light enhancing imaging, communication, and photonic ...

Optical cavities, also known as optical resonators, are structures that confine light within a small volume by utilizing highly reflective surfaces. These cavities allow light to circulate or bounce ...

A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive processors” was published by researchers at UCLA. “Nonlinear computation is ...